由于抑尘培训过程中火车进站不停车以及抑尘配料专业性高、危险性大等原因,铁路抑尘作业的现场培训一直备受关注。为了降低现场操作风险,采用Open Scene Graph(OSG)技术,开发了一套铁路抑尘系统虚拟仿真培训平台,并采用底层算法封装,模...由于抑尘培训过程中火车进站不停车以及抑尘配料专业性高、危险性大等原因,铁路抑尘作业的现场培训一直备受关注。为了降低现场操作风险,采用Open Scene Graph(OSG)技术,开发了一套铁路抑尘系统虚拟仿真培训平台,并采用底层算法封装,模块整合等技术实现了面向二次开发的API接口,方便了软件的升级扩展。针对抑尘喷淋过程中喷量实时变化的仿真难点,提出了基于粒子系统的喷淋仿真算法;并针对培训过程中所需要的声音效果,设计实现了基于OSGAL的实时虚拟反馈声效。经现场培训测试,平台能够满足培训的需要,解决了抑尘作业培训中的困难与不足。展开更多
Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumpti...Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumption. Our method contains two parts: one is an Enhanced Self-Organizing Background Subtraction (ESOBS) based foreground segmentation module to obtain active areas in the observed region from the visual sensors; the other is an appearance model based detection module to detect the pedestrians from the foreground areas. Moreover, we create our own large pedestrian dataset according to the specific scene in the visual sensor network. Numerous experiments are conducted in both indoor and outdoor specific scenes. The experimental results show that our method is effective.展开更多
文摘由于抑尘培训过程中火车进站不停车以及抑尘配料专业性高、危险性大等原因,铁路抑尘作业的现场培训一直备受关注。为了降低现场操作风险,采用Open Scene Graph(OSG)技术,开发了一套铁路抑尘系统虚拟仿真培训平台,并采用底层算法封装,模块整合等技术实现了面向二次开发的API接口,方便了软件的升级扩展。针对抑尘喷淋过程中喷量实时变化的仿真难点,提出了基于粒子系统的喷淋仿真算法;并针对培训过程中所需要的声音效果,设计实现了基于OSGAL的实时虚拟反馈声效。经现场培训测试,平台能够满足培训的需要,解决了抑尘作业培训中的困难与不足。
基金This paper was supported partially by the Natural Science Foundation of China under Grants No. 60833009, No. 61003280 the National Science Fund for Distinguished Young Scholars under Grant No. 60925010+1 种基金 the Funds for Creative Research Groups of China under Grant No.61121001 the Pro- gram for Changjiang Scholars and Innovative Research Team in University under Grant No. IRT1049.
文摘Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumption. Our method contains two parts: one is an Enhanced Self-Organizing Background Subtraction (ESOBS) based foreground segmentation module to obtain active areas in the observed region from the visual sensors; the other is an appearance model based detection module to detect the pedestrians from the foreground areas. Moreover, we create our own large pedestrian dataset according to the specific scene in the visual sensor network. Numerous experiments are conducted in both indoor and outdoor specific scenes. The experimental results show that our method is effective.
